


from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map






def 					UpperCamelCase   (      __magic_name__	:				Dict[str, torch.Tensor]	)  ->    Dict[str, torch.Tensor]:
		"""simple docstring"""




		lowercase__	     =						[]
		lowercase__	     =						[]
		lowercase__	     =						[]

		for rt in rc.restypes:
				lowercase__	     =						rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
				restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names]	)
				lowercase__	     =						{name: i for i, name in enumerate(__magic_name__	)}
				restype_atomaa_to_atomaa_list.append(
				    [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types]	)

				restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names]	)

		# Add dummy mapping for restype 'UNK'
		restype_atomaa_to_atomaa_list.append([0] * 14	)
		restype_atomaa_to_atomaa_list.append([0] * 37	)
		restype_atomaa_mask_list.append([0.0] * 14	)

		lowercase__	     =						torch.tensor(
		    __magic_name__       ,       dtype=torch.intaa       ,       device=protein["""aatype"""].device       ,       )
		lowercase__	     =						torch.tensor(
		    __magic_name__       ,       dtype=torch.intaa       ,       device=protein["""aatype"""].device       ,       )
		lowercase__	     =						torch.tensor(
		    __magic_name__       ,       dtype=torch.floataa       ,       device=protein["""aatype"""].device       ,       )
		lowercase__	     =						protein["""aatype"""].to(torch.long	)

		# create the mapping for (residx, atom14) --> atom37, i.e. an array
		# with shape (num_res, 14) containing the atom37 indices for this protein
		lowercase__	     =						restype_atomaa_to_atomaa[protein_aatype]
		lowercase__	     =						restype_atomaa_mask[protein_aatype]

		lowercase__	     =						residx_atomaa_mask
		lowercase__	     =						residx_atomaa_to_atomaa.long()

		# create the gather indices for mapping back
		lowercase__	     =						restype_atomaa_to_atomaa[protein_aatype]
		lowercase__	     =						residx_atomaa_to_atomaa.long()

		# create the corresponding mask
		lowercase__	     =						torch.zeros([21, 37]       ,       dtype=torch.floataa       ,       device=protein["""aatype"""].device	)
		for restype, restype_letter in enumerate(rc.restypes	):
				lowercase__	     =						rc.restype_atoa[restype_letter]
				lowercase__	     =						rc.residue_atoms[restype_name]
				for atom_name in atom_names:
						lowercase__	     =						rc.atom_order[atom_name]
						lowercase__	     =						1

		lowercase__	     =						restype_atomaa_mask[protein_aatype]
		lowercase__	     =						residx_atomaa_mask

		return protein







def 					UpperCamelCase   (      __magic_name__	:				Dict[str, torch.Tensor]	)  ->    Dict[str, np.ndarray]:
		"""simple docstring"""




		lowercase__	     =						tree_map(lambda __magic_name__	: torch.tensor(__magic_name__       ,       device=batch["""aatype"""].device	)       ,       __magic_name__       ,       np.ndarray	)
		lowercase__	     =						tensor_tree_map(lambda __magic_name__	: np.array(__magic_name__	)       ,       make_atomaa_masks(__magic_name__	)	)
		return out



from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def   _lowerCamelCase							(   self						:Tuple	,  a						:float		)						->					float:
								return 0.0




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     np.ndarray		,    _lowerCamelCase					:     int)   ->       tuple[int | float, int | float]:






							'''simple docstring'''





							__UpperCamelCase      :  List[str]       =   min([-20, np.min(fft_results[1 : samplerate // 2 - 1])])
							__UpperCamelCase      :  Any       =   max([20, np.max(fft_results[1 : samplerate // 2 - 1])])
							return lowest, highest




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     FilterType		,    _lowerCamelCase					:     int)   ->       None:






							'''simple docstring'''





							__UpperCamelCase      :  List[str]       =   512
							__UpperCamelCase      :  List[Any]       =   [1] + [0] * (size - 1)
							__UpperCamelCase      :  List[Any]       =   [filter_type.process(_lowerCamelCase) for item in inputs]

							__UpperCamelCase      :  Optional[Any]       =   [0] * (samplerate - size)  # zero-padding
							outputs += filler
							__UpperCamelCase      :  Optional[int]       =   np.abs(np.fft.fft(_lowerCamelCase))
							__UpperCamelCase      :  Optional[int]       =   20 * np.logaa(_lowerCamelCase)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24		,    samplerate / 2 - 1)
							plt.xlabel("Frequency (Hz)")
							plt.xscale("log")

							# Display within reasonable bounds
							__UpperCamelCase      :  Optional[Any]       =   get_bounds(_lowerCamelCase		,    _lowerCamelCase)
							plt.ylim(max([-80, bounds[0]])		,    min([80, bounds[1]]))
							plt.ylabel("Gain (dB)")

							plt.plot(_lowerCamelCase)
							plt.show()




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     FilterType		,    _lowerCamelCase					:     int)   ->       None:






							'''simple docstring'''





							__UpperCamelCase      :  Any       =   512
							__UpperCamelCase      :  Dict       =   [1] + [0] * (size - 1)
							__UpperCamelCase      :  Tuple       =   [filter_type.process(_lowerCamelCase) for item in inputs]

							__UpperCamelCase      :  Dict       =   [0] * (samplerate - size)  # zero-padding
							outputs += filler
							__UpperCamelCase      :  Optional[int]       =   np.angle(np.fft.fft(_lowerCamelCase))

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24		,    samplerate / 2 - 1)
							plt.xlabel("Frequency (Hz)")
							plt.xscale("log")

							plt.ylim(-2 * pi		,    2 * pi)
							plt.ylabel("Phase shift (Radians)")
							plt.plot(np.unwrap(_lowerCamelCase		,    -2 * pi))
							plt.show()